fulltext.study @t Gmail

Identification of critical genes in microarray experiments by a Neuro-Fuzzy approach

Paper ID Volume ID Publish Year Pages File Format Full-Text
15520 1420 2006 10 PDF Available
Title
Identification of critical genes in microarray experiments by a Neuro-Fuzzy approach
Abstract

Gene expression profiling by microarray technology is usually difficult to interpret into a simpler pattern. One approach to resolve the complexity of gene expression profiles is the application of artificial neural networks (ANNs). A potential difficulty in this strategy, however, is that the non-linear nature of ANN makes it essentially a ‘black-box’ computation process. Addition of a fuzzy logic approach is useful because it can complement ANN by explicitly specifying membership function during computation. We employed a hybrid approach of neural network and fuzzy logic to further analyze a published microarray study of gene responses to eight bacteria in human macrophages. The original analysis by hierarchical clustering found common gene responses to all bacteria but did not address individual responses. Our method allowed exploration of the gene response of the host to individual bacterium. We implemented a two-layer, feed-forward neural network containing the principle of ‘competitive learning’ (i.e. ‘winner-take-all’). The weights of the trained neural network were fed into a fuzzy logic inference system. A new measurement, called the impact rating (IR) was also introduced to explore the degree of importance of each gene. To assess the reliability of the IR value, a bootstrap re-sampling method was applied to the dataset and a confidence level for each IR was obtained. Our approach has successfully uncovered the unique features of host response to individual bacterium. Further, application of gene ontology (GO) annotation to the genes of high IR values in each response has suggested new biological pathways for individual host–pathogen interactions.

Keywords
Gene expression; Microarray; Gene ontology; Artificial networks; Fuzzy logic
First Page Preview
Identification of critical genes in microarray experiments by a Neuro-Fuzzy approach
Publisher
Database: Elsevier - ScienceDirect
Journal: Computational Biology and Chemistry - Volume 30, Issue 5, October 2006, Pages 372–381
Authors
, , ,
Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering